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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Correlation methods

A method for processing complex radar data with a computer using correlation functions is reviewed. Parameters including data storage, data reduction, and real time operation are addressed. Since complex auto- and cross-correlation functions are calculated and stored, almost no information is lost. These also can be analyzed in terms of the full correlation analysis of the spaced-antenna-drifts technique. The proposed approach therefore appears to be very feasible to suit most Mesosphere-Stratosphere-Troposphere (MST) radar applications.

Rottger, J.↗
NASA NTRS1985

High-speed holocinematographic velocimeter for studying turbulent flow control physics

Use of a dual view, high speed, holographic movie technique is examined for studying turbulent flow control physics. This approach, which eliminates some of the limitations of previous holographic techniques, is termed a holocinematographic velocimeter (HCV). The data from this system can be used to check theoretical turbulence modeling and numerical simulations, visualize and measure coherent structures in 'non-simple' turbulent flows, and examine the mechanisms operative in various turbulent control/drag reduction concepts. This system shows promise for giving the most complete experimental characterization of turbulent flows yet available.

Weinstein, L. M.↗
NASA NTRS1989

Nonprincipal plane scattering of flat plates and pattern control of horn antennas

Using the geometrical theory of diffraction, the traditional method of high frequency scattering analysis, the prediction of the radar cross section of a perfectly conducting, flat, rectangular plate is limited to principal planes. Part A of this report predicts the radar cross section in nonprincipal planes using the method of equivalent currents. This technique is based on an asymptotic end-point reduction of the surface radiation integrals for an infinite wedge and enables nonprincipal plane prediction. The predicted radar cross sections for both horizontal and vertical polarizations are compared to moment method results and experimental data from Arizona State University's anechoic chamber. In part B, a variational calculus approach to the pattern control of the horn antenna is outlined. The approach starts with the optimization of the aperture field distribution so that the control of the radiation pattern in a range of directions can be realized. A control functional is thus formulated. Next, a spectral analysis method is introduced to solve for the eigenfunctions from the extremal condition of the formulated functional. Solutions to the optimized aperture field distribution are then obtained.

Balanis, Constantine A.↗
NASA NTRS1989

Experimental determination of plume properties in full-scale hydrogen-oxygen rockets

An IR emission/absorption technique for determining radial profiles of static temperature and species partial pressure for cylindrically symmetric combustion gases typical of the effluent of turbine engines and liquid-propellant rockets is described. In the technique, the IR plume radiance and absorption is measured using a 1 x 256-element platinum silicide detector array which is filtered to obtain plume emission measurements in the H2O band near 3.0 microns. A minicomputer is employed to control data acquisition and reduction.

Brown, D. G.↗
NASA NTRS1993

An efficient liner cooling scheme for advanced small gas turbine combustors

A joint Army/NASA program was conducted to design, fabricate, and test an advanced, small gas turbine, reverse-flow combustor utilizing a compliant metal/ceramic (CMC) wall cooling concept. The objectives of this effort were to develop a design method (basic design data base and analysis) for the CMC cooling technique and then demonstrate its application to an advanced cycle, small, reverse-flow combustor with 3000 F burner outlet temperature. The CMC concept offers significant improvements in wall cooling effectiveness resulting in a large reduction in cooling air requirements. Therefore, more air is available for control of burner outlet temperature pattern in addition to the benefits of improved efficiency, reduced emissions, and lower smoke levels. The program was divided into four tasks. Task 1 defined component materials and localized design of the composite wall structure in conjunction with development of basic design models for the analysis of flow and heat transfer through the wall. Task 2 included implementation of the selected materials and validated design models during combustor preliminary design. Detail design of the selected combustor concept and its refinement with 3D aerothermal analysis were completed in Task 3. Task 4 covered detail drawings, process development and fabrication, and a series of burner rig tests. The purpose of this paper is to provide details of the investigation into the fundamental flow and heat transfer characteristics of the CMC wall structure as well as implementation of the fundamental analysis method for full-scale combustor design.

Paskin, Marc D.↗
NASA NTRS2002

Stability and Control Estimation Flight Test Results for the SR-71 Aircraft With Externally Mounted Experiments

A maximum-likelihood output-error parameter estimation technique is used to obtain stability and control derivatives for the NASA Dryden Flight Research Center SR-71A airplane and for configurations that include experiments externally mounted to the top of the fuselage. This research is being done as part of the envelope clearance for the new experiment configurations. Flight data are obtained at speeds ranging from Mach 0.4 to Mach 3.0, with an extensive amount of test points at approximately Mach 1.0. Pilot-input pitch and yaw-roll doublets are used to obtain the data. This report defines the parameter estimation technique used, presents stability and control derivative results, and compares the derivatives for the three configurations tested. The experimental configurations studied generally show acceptable stability, control, trim, and handling qualities throughout the Mach regimes tested. The reduction of directional stability for the experimental configurations is the most significant aerodynamic effect measured and identified as a design constraint for future experimental configurations. This report also shows the significant effects of aircraft flexibility on the stability and control derivatives.

Moes, Timothy R.↗
NASA NTRS2002

ISO Key Project: Exploring The Full Range of Quasar/AGN Properties

While most of the work on this program has been completed, as previously reported, the portion of the program dealing with the sub topic of ISO LWS data analysis and reduction for the LWS Extragalactic Science Team and its leader, Dr. Howard Smith, is still active. This program in fact continues to generate results, and newly available computer modeling has extended the value of the datasets, As a result the team has requested and been granted an obtained a no-cost extension to this program, through December 31, 2003. The essence of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic data bases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program has the following goals: (1) refine the data analysis of ISO observations, to obtain deeper and better SNR results on selected sources. The ISO data itself underwent "pipeline 10" reductions in early 2001, and additional "hands-on data reduction packages" were supplied by the ISO teams in 2001. The Fabry-Perot database in particularly sensitive to noise can slight calibration errors. (2) model the atomic and molecular line shapes, in particular the OH lines, using revised Monte-Carlo techniques developed by the SWAS team at the Center for Astrophysics; (3) attend scientific meetings and workshops; (4) do E&PO activities related to infrared astrophysics and/or spectroscopy.

Wilkes, Belinda↗
NASA NTRS2003

ISO Key Project: Exploring the Full Range of Quasar/Agn Properties

While most of the work on this program has been completed, as previously reported, the portion of the program dealing with the subtopic of ISO LWS data analysis and reduction for the LWS Extragalactic Science Team and its leader, Dr. Howard Smith, is still active. This program in fact continues to generate results, and newly available computer modeling has extended the value of the datasets. As a result the team requests a one-year no-cost extension to this program, through 31 December 2004. The essence of the proposal is to perform ISO spectroscopic studies, including data analysis and modeling, of star-formation regions using an ensemble of archival space-based data from the Infrared Space Observatory's Long Wavelength Spectrometer and Short Wavelength Spectrometer, but including as well some other spectroscopic databases. Four kinds of regions are considered in the studies: (1) disks around more evolved objects; (2) young, low or high mass pre-main sequence stars in star-formation regions; (3) star formation in external, bright IR galaxies; and (4) the galactic center. One prime focus of the program is the OH lines in the far infrared. The program has the following goals: 1) Refine the data analysis of ISO observations to obtain deeper and better SNR results on selected sources. The ISO data itself underwent 'pipeline 10' reductions in early 2001, and additional 'hands-on data reduction packages' were supplied by the ISO teams in 2001. The Fabry-Perot database is particularly sensitive to noise and slight calibration errors; 2) Model the atomic and molecular line shapes, in particular the OH lines, using revised Monte-Carlo techniques developed by the SWAS team at the Center for Astrophysics; 3) Attend scientific meetings and workshops; 4) Perform E&PO activities related to infrared astrophysics and/or spectroscopy.

Wilkes, Belinda↗
NASA NTRS2010

Advanced Navigation Strategies For Asteroid Sample Return Missions

Flyby and rendezvous missions to asteroids have been accomplished using navigation techniques derived from experience gained in planetary exploration. This paper presents analysis of advanced navigation techniques required to meet unique challenges for precision navigation to acquire a sample from an asteroid and return it to Earth. These techniques rely on tracking data types such as spacecraft-based laser ranging and optical landmark tracking in addition to the traditional Earth-based Deep Space Network radio metric tracking. A systematic study of navigation strategy, including the navigation event timeline and reduction in spacecraft-asteroid relative errors, has been performed using simulation and covariance analysis on a representative mission.

Getzandanner, K.↗
DOE OSTI2020

First Cosmology Results using Supernovae Ia from the Dark Energy Survey: Survey Overview, Performance, and Supernova Spectroscopy

We present details on the observing strategy, data-processing techniques, and spectroscopic targeting algorithms for the first three years of operation for the Dark Energy Survey Supernova Program (DES-SN). This five-year program using the Dark Energy Camera mounted on the 4 m Blanco telescope in Chile was designed to discover and follow supernovae (SNe) Ia over a wide redshift range (0.05 < z < 1.2) to measure the equation-of-state parameter of dark energy. We describe the SN program in full: strategy, observations, data reduction, spectroscopic follow-up observations, and classification. From three seasons of data, we have discovered 12,015 likely SNe, 308 of which have been spectroscopically confirmed, including 251 SNe Ia over a redshift range of 0.017 < z < 0.85. We determine the effective spectroscopic selection function for our sample and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. The data presented here are used for the first cosmology analysis by DES-SN (“DES-SN3YR”), the results of which are given in Dark Energy Survey Collaboration et al. The 489 spectra that are used to define the DES-SN3YR sample are publicly available at https://des.ncsa.illinois.edu/releases/sn.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2018

Plasmonic Hybrid Biocomposite as an Effective Substrate for Detection of Biomolecules by Surface-Enhanced Raman Spectroscopy

The enhancement of the Raman light scattering signal from the surface of the porous hybrid biocomposites based on polyhydroxybutyrate (PHB), calcium carbonate (CaCO{sub 3}), and nanoplasmonic Ag particles is investigated. Based on PHB, fibrous scaffolds are obtained by the electrospinning technique. The fibrous scaffolds have been covered by CaCO{sub 3} and Ag nanoparticles by means of mineralization in salt solutions and Ag reduction reaction. Successful formation of the CaCO{sub 3} and Ag nanoparticles on the scaffold surface has been confirmed by the data of scanning electron microscopy, x-ray diffraction analysis, and infrared spectroscopy. Surface-enhanced Raman spectroscopy (SERS) of the obtained sample surface has demonstrated a significant enhancement of the Rhodamine 6G signal (E{sub f} > 10{sup 5}) in comparison with the reference sample where the analyte concentration and the laser power were 100 times higher. Thus, the present research has confirmed prospects for the application of biocomposites based on polyhydroxybutyrate for detection and investigation of biomolecules by the SERS method.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A reforecasting-based dynamic reserve estimation for variable renewable generation and demand uncertainty

The installed capacity of renewables-based energy sources has been increasing in traditional power systems. In order to accommodate the increased variability and uncertainty associated with the deeper penetration of renewable sources like solar and wind, adjusted amounts of dynamic reserve are needed. Although probabilistic dynamic reserve estimation methods have been previously developed, most of them consider the uncertainty to be represented by parametric density functions that tend to perform poorly under extreme events and, moreover, neglect uncertainty introduced by the forecasting model itself. Toward addressing these limitations, this work presents, for the first time, a dynamic reserve estimation method for flexibility that incorporates nonparametric density estimation and a machine learning based reforecasting to provide a day-ahead prediction of the mean and spread of uncertainty around the base forecast. The prediction is, in turn, used to estimate the up and down reserve relative to the base forecast. Here, the present method takes various endogenous and exogenous features, including the calendar variables, as input to estimate the day-ahead reserve. Using a combination of reforecasting and dynamic reserve estimation techniques, the method is shown to adjust better to the dynamic nature of reserve requirements providing only what is needed to accommodate the expected deviations. Considering California Independent System Operator (CAISO) solar, wind and load data over an 18 month period, up to 67% reduction in the amount of reserve capacity needed for a one day reserve and reserve penalty for solar uncertainty is demonstrated. Additionally, the risk of reserve insufficiency in meeting the net demand is reduced by 20% with the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2024

Coated boron layers by boronization and a real-time boron coating using impurity powder dropper in LHD

In Large Helical Device (LHD), diborane (B 2 H 6 ) is used as a standard boron source for boronization, which is assisted by helium glow discharges. In 2019, a new Impurity Powder Dropper (IPD) system has been installed and is under evaluation as a real-time wall conditioning technique. In LHD), which is a large size heliotron device, an additional helium (He) glow discharge cleaning (GDC) after boronization has been operated for a reduction of hydrogen recycling from coated boron layers, and this operational time of 3 h was determined by spectroscopic data during glow discharges. A flat hydrogen profile is obtained on the top surface of coated boron on the specimen exposed to boronization, the result suggests a reduction of hydrogen at the top surface by He-GDC. Trapped oxygen in coated boron was obtained by boronization, and the coated boron, which has boron-oxide, on the first wall by B-IPD was also shown. Finally, considering the difference in coating areas between B 2 H 6 boronization and B-IPD operation, it would be most effective to use the IPD and B 2 H 6 boronization coating together for optimized wall conditioning.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

DDStore: Distributed Data Store for Scalable Training of Graph Neural Networks on Large Atomistic Modeling Datasets

Graph neural networks (GNNs) are a class of Deep Learning models used in designing atomistic materials for effective screening of large chemical spaces. To ensure robust prediction, GNN models must be trained on large volumes of atomistic data on leadership class supercomputers. Even with the advent of modern architectures that consist of multiple storage layers that include node-local NVMe devices in addition to device memory for caching large datasets, extreme-scale model training faces I/O challenges at scale.We present DDStore, an in-memory distributed data store designed for GNN training on large-scale graph data. DDStore provides a hierarchical, distributed, data caching technique that combines data chunking, replication, low-latency random access, and high throughput communication. DDStore achieves near-linear scaling for training a GNN model using up to 1000 GPUs on the Summit and Perlmutter supercomputers, and reaches up to a 6.15x reduction in GNN training time compared to state-of-the-art methodologies.

Choi, Jong Youl↗
DOE OSTI2025

Characterization and Quantification of Radiation-Induced Clusters/Precipitates in RPV Steels Using STEM-EDS and Machine Learning

Over the operational lifespan of a nuclear reactor, reactor pressure vessel (RPV) steels are subjected to significant neutron irradiation, resulting in complex microstructural changes and the consequent degradation of mechanical properties. Various physically motivated correlation models have been developed to predict neutron irradiation-induced embrittlement of RPVs under different irradiation conditions. However, the efficient and accurate characterizations and quantification of radiation-induced clusters in RPVs are still challenging, which will affect the precision of the predictive models for embrittlement of RPV components. In the DOE Visiting Faculty Program (VFP) research work at Oak Ridge National Lab (ORNL), I integrate machine learning to aid Scanning Transmission Electron Microscopy – Energy Dispersive X-ray Spectroscopy (STEM-EDS) analyses, which improve the characterization and quantification of radiation-induced clusters in RPV steels, thereby enabling more accurate predictions of material behavior under irradiation. The surveillance base- and welded- RPV steels were annealed at various temperatures of 340 °C, 450 °C and 500 °C for up to 168 hours, respectively. Afterwards, I have characterized radiation-induced clusters using advanced STEM-EDS techniques and subsequently applying machine learning algorithms to analyze and refine STEM-EDS datasets, enhancing the quantification of clusters compositions and distributions. In the end, an efficient workflow for integrating STEM-EDS data analysis with machine learning to address challenges including noise reduction has been developed. The completion of this VFP work will support bridge critical gaps in the accurate quantification of radiation-induced clusters in RPV steels using STEM-EDS and support the development of more precise models for predicting RPV embrittlement in the Light Water Reactor Sustainability program supported by Department of Energy and enhancing the collaboration between ORNL and Alred University. The outcome of the VFP project will leverage a few research papers submission to peer-reviewed journals in the relevant scientific field and a few oral presentations at national and international conferences.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1979

Preliminary noise tradeoff study of a Mach 2.7 cruise aircraft

NASA computer codes in the areas of preliminary sizing and enroute performance, takeoff and landing performance, aircraft noise prediction, and economics were used in a preliminary noise tradeoff study for a Mach 2.7 design supersonic cruise concept. Aerodynamic configuration data were based on wind-tunnel model tests and related analyses. Aircraft structural characteristics and weight were based on advanced structural design methodologies, assuming conventional titanium technology. The most advanced noise prediction techniques available were used, and aircraft operating costs were estimated using accepted industry methods. The 4-engines cycles included in the study were based on assumed 1985 technology levels. Propulsion data was provided by aircraft manufacturers. Additional empirical data is needed to define both noise reduction features and other operating characteristics of all engine cycles under study. Data on VCE design parameters, coannular nozzle inverted flow noise reduction and advanced mechanical suppressors are urgently needed to reduce the present uncertainties in studies of this type.

Mascitti, V. R.↗
NASA NTRS1980

State estimation and absolute image registration for geosynchronous satellites

Spacecraft state estimation and the absolute registration of Earth images acquired by cameras onboard geosynchronous satellites are described. The basic data type of the procedure consists of line and element numbers of image points called landmarks whose geodetic coordinates, relative to United States Geodetic Survey topographic maps, are known. A conventional least squares process is used to estimate navigational parameters and camera pointing biases from observed minus computed landmark line and element numbers. These estimated parameters along with orbit and attitude dynamic models are used to register images, using an automated grey level correlation technique, inside the span represented by the landmark data. In addition, the dynamic models can be employed to register images outside of the data span in a near real time mode. An important application of this mode is in support of meteorological studies where rapid data reduction is required for the rapid tracking and predicting of dynamic phenomena.

Nankervis, R.↗